Computational Empowerment

None

The course builds on the basic programming knowledge imparted in the course "Media Technology Basics" and is divided into two parts:

1) Computational Thinking and

2) Computational Empowerment Lab.

The aim of the course is to expand the knowledge acquired in the field of computational thinking to include contextual, human-related and social challenges and to stimulate creative and critical engagement with digital technologies. The students are encouraged to co-creatively deal with digital technologies.

Computational Thinking

In the first part of the course, the students receive an introduction to Python as a programming platform.
Using examples of specific applications and projects, the students get to know various possible uses of this language in the real world.
The exercises focus on different aspects of programming (input, output, math, conditionals, loops, functions, classes, object orientation).

Computational Empowerment Labs

As part of the Computational Empowerment Lab, students deal with those digital technologies and their fields of application that will be available to designers in the future and that must be included in the development of ideas: for example, 3D printers, cutting plotters, augmented and Virtual reality devices, robots, sensors and electronic kits, as well as AI applications.

Overall, the students are introduced to the interactions between technological and social developments and are empowered to reflect on the technological and communicative affordances of different media technologies. It is possible to apply the knowledge acquired in Python and digital fabrication as part of "Design Project 2" or to implement an individual project with a focus of your choice.

• The students have a basic understanding of programming and especially creative coding.
• They can name different programming languages ​​and development environments and assign areas of application.
• The students know Python as a programming language and platform and can name areas of application such as data visualization, IoT, computer vision, robotics, natural language processing and machine learning.
• They are familiar with open platforms in the open source and open hardware area, you can find resources and apply your own objectives and project contexts accordingly.
• They are able to apply creative problem-solving strategies digitally and know how to continuously expand your digital skills.
• The students are not only able to understand technology development, but also know the possibilities of actively helping to shape it.

Lecture / discussion / work in the laboratory

Examination and individual project work or implementation as part of the course "Design Project 2"

None

• K-12 Computer Science Framework: www.k12cs.org
• Iversen, Ole S.; Smith, Rachel C.; Dindler, Christian (2018): From Computational Thinking to Computational Empowerment. A 21^st Century PD Agenda. Proceedings of the 15^th Participatory Design Conference.
• Ernesti, Johannes; Kaiser, Peter (2015): Python 3. Das umfassende Handbuch. [Einführung, Praxis, Referenz; Sprachgrundlagen, Objektorientierung, Modularisierung; Migration, Debugging, Webentwicklung mit Django, GUIs, Netzwerkkommunikation u.v.m.] (4., aktualisierte und erweiterte Auflage ed.). Rheinwerk Verlag.
• Dörn, Sebastian (2020): Python lernen in abgeschlossenen Lerneinheiten. Programmieren für Einsteiger mit vielen Beispielen. Wiesbaden: Springer Fachmedien.

Face-to-face instruction